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The purpose of this paper is to analyse the stray losses in the windings of permanent magnet synchronous machines (PMSM).

The 2D field model, based on the edge element method (EEM) and

-V formulation, has been developed and utilized for the determination and analysis of stray losses in the PMSM with concentrated windings made of strip conductors. The influence of the supply frequency as well as the slot opening width on the losses caused by eddy currents has been examined. The different arrangements of the conductors in the tape wound coils have been studied. The obtained results have been compared to the reference case when the eddy current effect is neglected.

The usefulness of the proposed methodology of the stray losses evaluation has been tested on the case study problem. It has been observed that the stray losses in the windings of the considered machine can be reduced by choosing the proper value of the slot opening. The dependence of the stray losses on the frequency of the supply currents has been examined. The obtained results show that with the increase of frequency the stray losses caused by the eddy currents in the strip conductors increase.

The proposed 2D field numerical model makes it possible to analyse the stray losses in the tape wound concentrated windings of the PMSM motor. The presented model can be utilized for the optimization of the magnetic circuit of the machine with the aim of minimizing eddy current losses.

This paper aims to investigate an efficient approach to model the electromagnetic behaviors and predict stray-field loss inside the magnetic steel plate under 3D harmonic magnetization conditions so as to effectively prevent the structural components from local overheating and insulation damage in electromagnetic devices.

An experimental setup is applied to measure all the magnetic properties of magnetic steel plate under harmonic excitations with different frequencies and phase angles. The measurement and numerical simulation are carried out based on the updated TEAM Problem 21 Model B+ (P210-B+), under the 3D harmonic magnetization conditions. An improved method to evaluate the stray-field loss is proposed, and harmonic flux distribution in the structural components is analyzed.

The influence of the harmonic order and phase angle on the stray-field loss in magnetic steel components are noteworthy. Based on the engineering-oriented benchmark models, the variations of stray-field losses and magnetic field distribution inside the magnetic components under harmonic magnetization conditions are presented and analyzed in detail.

The capacity of the multi-function harmonic source, used in this work, was not large enough, which limits the magnetization level. Up to now, further improvements to increase the harmonic source capacity and investigations of the electromagnetic behaviors of magnetic steel components under multi-harmonic and DC-AC hybrid excitations are in progress.

To accurately predict the stray-field loss in magnetic steel plate, the improved method based on the combination of magnetic measurement and numerical simulation is proposed. The effects of the frequency and phase angle on the stray-field loss are analyzed.

The purpose of this paper is to apply a 3D methodology to assess the heating hazard on transformer covers and present a practical tool to design amagnetic inserts arrangement.

A practical 3D methodology linking an electromagnetic analytical formulation with thermal finite element method is used for computation. Such methodology allows the evaluation of the temperature on metallic device elements heated by electromagnetic induction. This is a 3D problem which in the case of power transformers becomes especially difficult to apply due to the discretization requirement into the thin skin depth penetration compared to big machine dimensions.

From the numerical solution of the temperature field, decisions on dimensions and different amagnetic inserts arrangements can be taken to avoid hot spots on transformer covers.

Some parameters presented in the model as heat exchange coefficients and material properties are difficult to determine from formulae or from the literature. The accuracy of the results strongly depends on the proper identification of those parameters, which the authors adjust based on measurements.

Differing from previous works found in the literature, which focus their results in power loss computation methods, this paper evaluates losses in terms of temperature distribution, which is easier to measure and validate over transformer covers. Moreover, an experimental work is presented where the temperature distribution is measured over a steel cover plate and a cover plate with amagnetic insert.

The purpose of this paper is to present a simple and effective method to search the optimal turn-on and turn-off angles on-line for the control of the switched reluctance motor (SRM). The optimal turn-on and turn-off angles are defined as the ones that can meet torque production requirements with minimum copper loss.

The optimal turn-on and turn-off angles are first defined based on the analysis of the SRM losses and torque production principles. Then the algorithm for optimal angles searching is developed, and the searching parameters are determined through analytical computation. The optimal angles are approached on-line with iterative process. Simulation and experiments are finally performed to verify the proposed method.

The presented method can meet torque production requirements while copper loss is minimized. The optimal turn-on and turn-off angles are generally approached within five phase cycles for most of the SRM operation modes. Furthermore, the SRM drive system using the presented method exhibits good dynamics during starting and sudden load operations.

The presented method is simple, and implementation of it is easy. It is an eligible candidate for industrial applications where energy conversion efficiency is crucial.

The optimal turn-off angle definition that considers both torque production and copper loss minimization is proposed. The turn-on and turn-off angles are searched independently on-line with little SRM geometrical information. The searching steps are derived through analytical computation and qualitative analysis so that both the searching speed and algorithm convergence are balanced.

The purpose of this paper is to present the application of an adaptive bacterial foraging (BF) algorithm for the design optimization of an energy efficient induction motor.

The induction motor design problem is formulated as a mixed integer nonlinear optimization problem. A set of nine independent variables is selected, and to make the machine feasible and practically acceptable, six constraints are imposed on the design. Two different objective functions are considered, namely, the annual active material cost, and the sum of the annual active material cost, annual cost of the active power loss of the motor and annual energy cost required to supply such power loss. A new adaptive BF algorithm is used for solving the optimization problem. A generic penalty function method, which does not require any penalty coefficient, is employed for constraint handling.

The adaptive BF algorithm is validated for two sample motors and benchmarked with the genetic algorithm, particle swarm optimization, simple BF algorithm, and conventional design methods. The results show that the proposed algorithm outperforms the other methods in both the solution quality and convergence rate. The annual cost of the induction motor is remarkably reduced when designed on the basis of minimizing its annual total cost, instead of minimizing its material cost only.

To the best of the knowledge, none of the existing work has applied the BF algorithms for electrical machine design problems. Therefore, the solution to this problem constitutes the main contribution of the paper. According to the huge number of induction motors operating all over the world, the BF techniques used in their design, on minimum annual cost basis, will lead to a tremendous saving in global energy consumption.

Improvements on the energy efficiency of the induction motors bear on not only these motors but also on the whole industry as a result of preference of these types of motors. In recent projects, energy efficiency of the induction motors is approaching to 90 per cent. The first necessary condition of the efficiency improvements is an accurate estimation of energy efficiency. This study aims to estimate the energy efficiency of induction motors by using three innovative estimation methods.

Data for 307 motors were taken from three different companies and their torque, power, power factor and speed data were used. Three hybrid models were created by estimating the error of three autoregressive (AR)-based efficiency estimation models with the back-propagation artificial neural network (ANN) structure. In these proposed hybrid models, the AR models were supported with artificial neural networks to obtain a minimum estimation error. These three hybrid models were called as AR1-ANN, AR4-ANN and residual-ANN.

Without hybridization of AR models by back-propagation ANNs, the best estimation result was obtained by residual model. On the other hand, for the proposed hybrid models, the best estimation was obtained by AR1-ANN, followed by AR4-ANN and finally the residual-ANN according to ME values.

Proposed AR-ANN hybrid models relieve of longtime experiments for the energy efficiency measurement of induction motors. Furthermore, these AR-ANN models give more accurate results than the available methods in the literature. Engineering value of this research is three different issues in finding energy efficiency. The first one is minimizing of the test cost, the second one is no requirement the test equipment and the third one is not interrupting the motor. Every company that needs motors can use these estimation methods due to the advantages.

Novel three AR-ANN hybrid models for energy efficiency estimation were studied. These novel methods give better response than the other methods which were used for estimation of induction motors in the literature.

This paper aims to give a perspective about the variety of techniques which are available and are being further developed in the area of coupled field formulations, with selective bibliography and practical examples, to help postgraduate students, researchers and designers working in design or analysis of electrical machinery.

This paper reviews the recent trends in coupled field formulations. The use of these formulations for designing and non‐destructive testing of electrical machinery is described, followed by their classifications, solutions and applications. Their advantages and shortcomings are discussed.

The paper gives an overview of research, development and applications of coupled field formulations for electrical machinery based on more than 160 references. All landmark papers are classified. Practical engineering case studies are given which illustrate wide applicability of coupled field formulations.

Problems which continue to pose challenges to researchers are enumerated and the advantages of using the coupled‐field formulation are pointed out.

This paper gives a detailed description of the application of the coupled field formulation method to the analysis of problems that are present in different electrical machines. Examples of analysis of generators and transformers with this formulation are presented. The application examples give guidelines for its use in other analyses.

The coupled‐field formulation is used in the analysis of rotational machines and transformers where reference data are available and comparisons with other methods are performed and the advantages are justified. This paper serves as a guide for the ongoing research on coupled problems in electrical machinery.

This paper tests the eddy current analysis methods based on TEAM benchmark model, evaluates the engineering effectiveness of the eddy current codes through product‐based test models, and proposes an engineering‐oriented loss solver to deal with the eddy current loss problems concerning the core tie‐plates in large power transformers.

In this paper, we applied the finite element modeling to the stator temperature distribution of a hydroelectric generator. The electrical losses produce a temperature distribution in the stator of a synchronous generator. For the calculation and optimization of the temperature distribution, a full parameterized thermal model of the stator was created using the finite element method. Now it is possible to calculate the thermal effects of different parameter modifications and additionally we can optimize the heat transfer for the stator with variant calculations. The most important bar fitting systems and its thermal efforts are included in this thermal stator model. Our targets are to decrease the expensive and time‐consuming laboratory measurements in the future and improve the accuracy of the standard calculation software. To estimate the accuracy of the finite element model we build an additional laboratory model.

To improve the power density and generation efficiency of the tubular permanent magnetic linear generators (TPMLGs) under realistic sea-stator condition, a TPMLG with 120° phase belt toroidal windings (120°-TPMLG) for wave energy conversion is proposed in this paper.

First, the structure of the 120°-TPMLG is introduced and its operation principle is analyzed. Second, the design process of the 120°-TPMLG is described. Meanwhile, the finite-element models of the 120°-TPMLG and the TPMLG with traditional fractional pitch windings (T-TPMLG) are established based on the similar overall dimensions. Then, the electromagnetic characteristics of the 120°-TPMLG are analyzed, such as air gap flux density, back electromotive force and load voltage. Finally, a comparative analysis of the magnetic flux density, flux linkage, load and no-load performance of the two generators are conducted.

The result shows that the 120°-TPMLG has higher power density and generation efficiency than the T-TPMLG.

This paper proposes a TPMLG with 120° phase belt toroidal windings (120°-TPMLG) to improve the power density and generation efficiency.